Principal Data Scientist - Machine Learning Expert

- Advanced proficiency in Python with substantial experience in data science libraries such as pandas, numpy, scikit-learn, and statsmodels - Proven experience in developing and deploying time-series forecasting models, such as ARIMA, SARIMAX, and gradient boosting methods - Demonstrated ability to transition models from research and development to production deployment, including versioning, monitoring, and maintenance - Experience integrating weather APIs and external data sources into forecasting pipelines, along with a strong background in data engineering - Familiarity with AWS services like EC2, S3, Lambda, and SageMaker, as well as Infrastructure-as-Code practices - Proficient in managing SQL databases and conducting large-scale data queries and optimization - Experience crafting interactive dashboards utilizing Streamlit, Plotly, or similar frameworks for effective stakeholder communication - Expertise in feature engineering utilizing weather data and domain-specific signals - Knowledge of model evaluation metrics including MAE, RMSE, and MAPE - Proficiency in creating automated data pipelines and employing version control using Git